| 基于差异演化的粒子群优化算法 |
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| 引用本文： | 郭广寒,王志刚,郝志峰.基于差异演化的粒子群优化算法[J].哈尔滨商业大学学报(自然科学版),2008,24(3):290-292. |
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| 作者姓名： | 郭广寒 王志刚 郝志峰 |
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| 作者单位： | 1. 华南理工大学,数学科学学院,广州,510640
2. 华南理工大学,数学科学学院,广州,510640;华南理工大学,计算机科学与工程学院,广州,510640 |
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| 基金项目： | 教育部跨世纪优秀人才培养计划
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广东省自然科学基金 |
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| 摘 要： | 针对粒子群优化算法由于缺乏种群多样性而导致早熟收敛的不利因素.提出了一种把差异演化算法中的后代产生机制引入粒子群优化算法的更新规则中以保持粒子群的种群多样性和加快收敛速度的算法.这种思想能有效改善摆脱极值点的能力.基于几个高维测试函数的试验结果显示,该算法在收敛速度快和精度方面都优于粒子群优化算法.
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| 关 键 词： | 粒子群优化算法 差异演化算法 种群多样性 测试 全局连续优化 |
| 文章编号： | 1672-0946(2008)03-0290-03 |
| 修稿时间： | 2007年7月12日 |
Particle swarm optimization based on differential evolution |
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| GUO Guang-han,WANG Zhi-gang,HAO Zhi-feng.Particle swarm optimization based on differential evolution[J].Journal of Harbin University of Commerce :Natural Sciences Edition,2008,24(3):290-292. |
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| Authors: | GUO Guang-han WANG Zhi-gang HAO Zhi-feng |
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| Institution: | GUO Guang-han ,WANG Zhi-gang, HAO Zhi-feng ( 1. School of Mathematical Science, South China University of Technology, Guangzhou 510640, China; 2. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510640, China) |
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| Abstract: | Considering particle swarm optimization （PSO） being easily trapped in local optima because of the loss of population diversity, an algorithm that DE offspring generation scheme is introduced in the update rules of PSO in order to maintain the population diversity and accelerate the converging speed is proposed in this paper. This strategy can improve the ability of escaping the local optima effectively. Simulation results on a suite of benchmark functions show that the proposed algorithm is superior to original particle swarm optimization algorithm. |
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| Keywords: | particle swarm optimization differential evolution diversity of population testing global continuous optimization |
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